A comprehensive decision-making structure for acceptance/rejection of incoming orders in make-to-order environments

Several incoming orders must be considered and evaluated in terms of many different conflicting criteria for acceptance/rejection in a make-to-order manufacturing system, leading to a large set of subjective or ambiguous data. Hence, an effective evaluation approach is essential to improve decision quality. In this paper, a comprehensive decision-making structure composed of two phases is proposed to manage incoming orders. At the first phase, the new arriving orders are evaluated based on their due dates and material arrival times. At the second phase, a novel hybrid methodology consisting of analytic hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS) is presented for acceptance or rejection of the first phase accepted orders based on the manufacturing system capacity. In this study the rating of each alternative regarding different criteria (throughout the TOPSIS technique) is described by means of linguistic variables. Furthermore we apply fuzzy AHP methodology to determine the relative weights of evaluation criteria. At the end, the effectiveness of the proposed model is demonstrated through a case study.